Identification of instabilities in rotorcraft systems

Siddharth Sonti, Joseph Horn, Eric Keller, Asok Ray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This short paper presents a data-driven method for identification of stability margin in rotorcraft system dynamics and the underlying concept is built upon the principles of Symbolic Dynamics. The algorithm involves wavelet-packet-based preprocessing to remove spurious disturbances and to improve the signal-to-noise ratio (SNR) of sensor time series. A quantified measure, called Instability Measure, is constructed from the processed time series data to obtain an estimate of the relative instability of the dynamic modes of interest on the rotorcraft system. The proposed method has been tested with numerical simulations; and correlations between the Instability Measure and the damping parameters of selected dynamic modes of the rotor blade have been established.

Original languageEnglish (US)
Title of host publicationAerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Print)9780791856123
DOIs
StatePublished - Jan 1 2013
EventASME 2013 Dynamic Systems and Control Conference, DSCC 2013 - Palo Alto, CA, United States
Duration: Oct 21 2013Oct 23 2013

Publication series

NameASME 2013 Dynamic Systems and Control Conference, DSCC 2013
Volume1

Other

OtherASME 2013 Dynamic Systems and Control Conference, DSCC 2013
CountryUnited States
CityPalo Alto, CA
Period10/21/1310/23/13

Fingerprint

Time series
Turbomachine blades
Signal to noise ratio
Dynamical systems
Rotors
Damping
Sensors
Computer simulation

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Sonti, S., Horn, J., Keller, E., & Ray, A. (2013). Identification of instabilities in rotorcraft systems. In Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications; [V001T01A001] (ASME 2013 Dynamic Systems and Control Conference, DSCC 2013; Vol. 1). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DSCC2013-3784
Sonti, Siddharth ; Horn, Joseph ; Keller, Eric ; Ray, Asok. / Identification of instabilities in rotorcraft systems. Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;. American Society of Mechanical Engineers (ASME), 2013. (ASME 2013 Dynamic Systems and Control Conference, DSCC 2013).
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Sonti, S, Horn, J, Keller, E & Ray, A 2013, Identification of instabilities in rotorcraft systems. in Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;., V001T01A001, ASME 2013 Dynamic Systems and Control Conference, DSCC 2013, vol. 1, American Society of Mechanical Engineers (ASME), ASME 2013 Dynamic Systems and Control Conference, DSCC 2013, Palo Alto, CA, United States, 10/21/13. https://doi.org/10.1115/DSCC2013-3784

Identification of instabilities in rotorcraft systems. / Sonti, Siddharth; Horn, Joseph; Keller, Eric; Ray, Asok.

Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;. American Society of Mechanical Engineers (ASME), 2013. V001T01A001 (ASME 2013 Dynamic Systems and Control Conference, DSCC 2013; Vol. 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This short paper presents a data-driven method for identification of stability margin in rotorcraft system dynamics and the underlying concept is built upon the principles of Symbolic Dynamics. The algorithm involves wavelet-packet-based preprocessing to remove spurious disturbances and to improve the signal-to-noise ratio (SNR) of sensor time series. A quantified measure, called Instability Measure, is constructed from the processed time series data to obtain an estimate of the relative instability of the dynamic modes of interest on the rotorcraft system. The proposed method has been tested with numerical simulations; and correlations between the Instability Measure and the damping parameters of selected dynamic modes of the rotor blade have been established.

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Sonti S, Horn J, Keller E, Ray A. Identification of instabilities in rotorcraft systems. In Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;. American Society of Mechanical Engineers (ASME). 2013. V001T01A001. (ASME 2013 Dynamic Systems and Control Conference, DSCC 2013). https://doi.org/10.1115/DSCC2013-3784